def test_actual_to_renate_idl(self):
for test_case in self.test_cases:
path = os.path.join('test_dataset', 'crm_systemtests', 'archive',
'renate_idl', test_case + '.xml')
reference = Beamlet(data_path=path, solver='disregard')
actual_source = reference.copy(object_copy='without-results')
actual = Beamlet(param=actual_source.param,
profiles=actual_source.profiles,
components=actual_source.components,
atomic_db=actual_source.atomic_db,
solver='numerical')
msg = 'Failure for following test case: ' + test_case + '\n'
self.assertAlmostEqualRateEvolution(
actual, reference, precision=self.EXPECTED_PRECISION, msg=msg)
def test_profiles(self):
actual = Beamlet(solver='disregard')
self.assertIsInstance(
actual.profiles,
pandas.core.frame.DataFrame,
msg='Expected data type of profiles is: pandas DataFrame.')
self.assertEqual(
len(actual.profiles),
self.EXPECTED_PROFILES_LENGTH,
msg='Expected profile length for test case does not match.')
self.assertTupleEqual(
actual.profiles.shape,
(self.EXPECTED_PROFILES_LENGTH,
2 * len(self.EXPECTED_COMPONENTS_KEYS) + 1),
msg='Plasma description lacks necessary'
' density and/or temperature profiles for all components.')
self.assertIsInstance(
actual.profiles.axes[0],
pandas.Int64Index,
msg='Expected data type of X - axis for profiles is Int64Index.')
self.assertIsInstance(
actual.profiles.axes[1],
pandas.MultiIndex,
msg='Expected data type of Y - axis for profiles is MultiIndex.')
for key in range(len(actual.profiles.keys())):
self.assertTupleEqual(
actual.profiles.keys()[key],
self.EXPECTED_PROFILES_KEYS[key],
msg='Profiles key description fails for test case.')
def _compute_all_benchmarks(self):
for test_case in self.test_cases:
test_path = self.test_path + '/' + self.actual_folder + '/' + test_case + '.xml'
reference = Beamlet(data_path=test_path, solver='disregard')
actual_source = reference.copy(object_copy='without-results')
actual = Beamlet(param=actual_source.param,
profiles=actual_source.profiles,
components=actual_source.components,
atomic_db=actual_source.atomic_db,
solver='numerical')
actual.compute_linear_density_attenuation()
actual.compute_linear_emission_density()
actual.compute_relative_populations()
self.write.write_beamlet_profiles(actual,
subdir=self.release_folder + '/')
def test_actual_to_previous_release(self):
for test_case in self.test_cases:
path = os.path.join('test_dataset', 'crm_systemtests', 'actual',
test_case + '.xml')
reference = Beamlet(data_path=path, solver='disregard')
actual_source = reference.copy(object_copy='without-results')
actual = Beamlet(param=actual_source.param,
profiles=actual_source.profiles,
components=actual_source.components,
atomic_db=actual_source.atomic_db,
solver='numerical')
msg = 'Failure for following test case: ' + test_case + '\n'
self.assertAlmostEqualRateEvolution(
actual, reference, precision=self.EXPECTED_PRECISION, msg=msg)
actual.compute_linear_density_attenuation()
self.assertAlmostEqualBeamAttenuation(
actual, reference, precision=self.EXPECTED_PRECISION, msg=msg)
actual.compute_linear_emission_density()
self.assertAlmostEqualEmissionDensity(
actual, reference, precision=self.EXPECTED_PRECISION, msg=msg)
actual.compute_relative_populations()
self.assertAlmostEqualRelativePopulation(
actual, reference, precision=self.EXPECTED_PRECISION, msg=msg)
def __init__(self, plasma, beam):
# TODO - input variable validation
# build species specifications, starting with electrons
charges = [-1]
charges.extend(
[s.charge for s in plasma.composition if not s.charge == 0])
nuclear_charges = [0]
nuclear_charges.extend([
s.element.atomic_number for s in plasma.composition
if not s.charge == 0
])
atomic_weights = [0]
atomic_weights.extend([
int(s.element.atomic_weight) for s in plasma.composition
if not s.charge == 0
])
index = ['electron']
index.extend(
['ion{}'.format(i + 1) for i in range(len(atomic_weights) - 1)])
components = pd.DataFrame(data={
'q': charges,
'Z': nuclear_charges,
'A': atomic_weights
},
index=index)
# sample plasma parameters along the beam axis
beam_axis = np.linspace(0, beam.length, num=500)
beam_to_world = beam.to_root()
num_params = 1 + 2 + len(
plasma.composition
) * 2 # *2 since every species has density and temperature
profiles = np.zeros((num_params, 500))
type_labels = []
property_labels = []
unit_labels = []
profiles[0, :] = beam_axis
type_labels.append('beamlet grid')
property_labels.append('distance')
unit_labels.append('m')
profiles[1, :] = _sample_along_beam_axis(
plasma.electron_distribution.density,
beam_axis,
beam_to_world,
debug=True)
type_labels.append('electron')
property_labels.append('density')
unit_labels.append('m-3')
profiles[2, :] = _sample_along_beam_axis(
plasma.electron_distribution.effective_temperature, beam_axis,
beam_to_world)
type_labels.append('electron')
property_labels.append('temperature')
unit_labels.append('eV')
for i, species in enumerate(plasma.composition):
profiles[i * 2 + 3, :] = _sample_along_beam_axis(
species.distribution.density, beam_axis, beam_to_world)
type_labels.append('ion{}'.format(i))
property_labels.append('density')
unit_labels.append('m-3')
profiles[i * 2 + 4, :] = _sample_along_beam_axis(
species.distribution.effective_temperature, beam_axis,
beam_to_world)
type_labels.append('ion{}'.format(i))
property_labels.append('temperature')
unit_labels.append('eV')
profiles = np.swapaxes(profiles, 0, 1)
row_index = [i for i in range(500)]
column_index = pd.MultiIndex.from_arrays(
[type_labels, property_labels, unit_labels],
names=['type', 'property', 'unit'])
profiles = pd.DataFrame(data=profiles,
columns=column_index,
index=row_index)
# construct beam param specification
xml = etree.Element('xml')
head = etree.SubElement(xml, 'head')
id_tag = etree.SubElement(head, 'id')
id_tag.text = 'beamlet_test'
body_tag = etree.SubElement(xml, 'body')
beamlet_energy = etree.SubElement(body_tag, 'beamlet_energy',
{'unit': 'keV'})
beamlet_energy.text = str(int(beam.energy / 1000))
beamlet_species = etree.SubElement(body_tag, 'beamlet_species')
beamlet_species.text = beam.element.symbol
beamlet_source = etree.SubElement(body_tag, 'beamlet_source')
beamlet_source.text = 'beamlet/test_impurity.h5'
beamlet_current = etree.SubElement(body_tag, 'beamlet_current',
{'unit': 'A'})
beamlet_current.text = '0.001'
beamlet_mass = etree.SubElement(body_tag, 'beamlet_mass',
{'unit': 'kg'})
beamlet_mass.text = '1.15258e-026'
beamlet_velocity = etree.SubElement(body_tag, 'beamlet_velocity',
{'unit': 'm/s'})
beamlet_velocity.text = '1291547.1348855693'
beamlet_profiles = etree.SubElement(body_tag, 'beamlet_profiles', {})
beamlet_profiles.text = './beamlet_test.h5'
param = etree.ElementTree(element=xml)
# move this outside
# from crm_solver.atomic_db import AtomicDB
# renata_ad = AtomicDB(param=param)
b = Beamlet(param=param, profiles=profiles, components=components)
b.compute_linear_density_attenuation()
b.compute_relative_populations()
self.renate_beamlet = b
xml = etree.Element('xml')
head = etree.SubElement(xml, 'head')
id_tag = etree.SubElement(head, 'id')
id_tag.text = 'beamlet_test'
body_tag = etree.SubElement(xml, 'body')
beamlet_energy = etree.SubElement(body_tag, 'beamlet_energy', {'unit': 'keV'})
beamlet_energy.text = '100'
beamlet_species = etree.SubElement(body_tag, 'beamlet_species')
beamlet_species.text = 'H' # Li
beamlet_source = etree.SubElement(body_tag, 'beamlet_source')
beamlet_source.text = 'beamlet/test_impurity.h5'
beamlet_current = etree.SubElement(body_tag, 'beamlet_current', {'unit': 'A'})
beamlet_current.text = '0.001'
beamlet_mass = etree.SubElement(body_tag, 'beamlet_mass', {'unit': 'kg'})
beamlet_mass.text = '1.15258e-026'
beamlet_velocity = etree.SubElement(body_tag, 'beamlet_velocity',
{'unit': 'm/s'})
beamlet_velocity.text = '1291547.1348855693'
beamlet_profiles = etree.SubElement(body_tag, 'beamlet_profiles', {})
beamlet_profiles.text = './beamlet_test.h5'
param = etree.ElementTree(element=xml)
b = Beamlet(param=param, profiles=profiles, components=components)
b.compute_linear_emission_density()
b.compute_linear_density_attenuation()
b.compute_relative_populations()
plt.plot(b.profiles['beamlet grid'], b.profiles['linear_emission_density'])
class BeamletTest(unittest.TestCase):
EXPECTED_ATTR = [
'param', 'components', 'profiles', 'coefficient_matrix', 'atomic_db',
'initial_condition'
]
EXPECTED_INITIAL_CONDITION = [
4832583106.4753895, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
]
EXPECTED_PARAM_ATTR = [
'beamlet_source', 'beamlet_energy', 'beamlet_species',
'beamlet_current'
]
EXPECTED_COMPONENTS_KEYS = ['q', 'Z', 'A']
EXPECTED_COMPONENTS_SPECIES = ['electron', 'ion1', 'ion2']
EXPECTED_PROFILES_LENGTH = 101
EXPECTED_PROFILES_KEYS = [('beamlet grid', 'distance', 'm'),
('electron', 'density', 'm-3'),
('electron', 'temperature', 'eV'),
('ion1', 'density', 'm-3'),
('ion1', 'temperature', 'eV'),
('ion2', 'density', 'm-3'),
('ion2', 'temperature', 'eV')]
EXPECTED_ATTENUATION_KEY = 'linear_density_attenuation'
INPUT_TRANSITION = ['2s', '2p', '5s', '5p']
EXPECTED_ELEMENTS_3 = 3
def setUp(self):
self.beamlet = Beamlet()
def tearDown(self):
del self.beamlet
def test_attributes(self):
for attr in self.EXPECTED_ATTR:
assert hasattr(self.beamlet, attr)
def test_initial_conditions(self):
self.assertIsInstance(self.beamlet.initial_condition,
list,
msg='Initial condition is of wrong type. '
'Expected type: list')
self.assertEqual(
len(self.beamlet.initial_condition),
self.beamlet.atomic_db.atomic_ceiling,
msg='Initial conditions must match number of atomic levels.')
for element in range(len(self.beamlet.initial_condition)):
self.assertIsInstance(self.beamlet.initial_condition[element],
float,
msg='Expected type for initial'
' conditions is float.')
self.assertEqual(
self.beamlet.initial_condition[element],
self.EXPECTED_INITIAL_CONDITION[element],
msg=
'Computed Init conditions do not match expected init conditions.'
)
def test_param_xml(self):
self.assertIsInstance(
self.beamlet.param,
etree._ElementTree,
msg='Expected type for param input is xml elementtree.')
for param_attribute in self.EXPECTED_PARAM_ATTR:
self.assertIsInstance(self.beamlet.param.getroot().find(
'body').find(param_attribute).text,
str,
msg='Failed to load or find attribute ' +
param_attribute + ' in xml file.')
def test_atomic_db(self):
self.assertIsInstance(
self.beamlet.atomic_db,
AtomicDB,
msg='Expected data type for the Atomic database is AtomicDB.')
def test_components(self):
self.assertIsInstance(
self.beamlet.components,
pandas.core.frame.DataFrame,
msg='Expected data type of components is: pandas DataFrame.')
description = self.beamlet.components.keys()
species = self.beamlet.components.T.keys()
self.assertEqual(
len(description),
self.EXPECTED_ELEMENTS_3,
msg='Three keys are expected for species description: q,Z,A.')
for key in range(len(description)):
self.assertEqual(description[key],
self.EXPECTED_COMPONENTS_KEYS[key],
msg='The index: ' + description[key] +
' is a mismatch for ' +
self.EXPECTED_COMPONENTS_KEYS[key])
self.assertEqual(
len(species),
len(self.beamlet.atomic_db.ion_impact_loss[0]) + 1,
msg=
'The same amount of species description have to be present in components as in profiles.'
)
for key in range(len(species)):
self.assertEqual(species[key],
self.EXPECTED_COMPONENTS_SPECIES[key],
msg='Mismatch of expected plasma species.')
for component in species:
for coordinate in description:
self.assertIsInstance(
self.beamlet.components[coordinate][component],
numpy.int64,
msg='Type mismatch of pandas components content.')
def test_profiles(self):
actual = Beamlet(solver='disregard')
self.assertIsInstance(
actual.profiles,
pandas.core.frame.DataFrame,
msg='Expected data type of profiles is: pandas DataFrame.')
self.assertEqual(
len(actual.profiles),
self.EXPECTED_PROFILES_LENGTH,
msg='Expected profile length for test case does not match.')
self.assertTupleEqual(
actual.profiles.shape,
(self.EXPECTED_PROFILES_LENGTH,
2 * len(self.EXPECTED_COMPONENTS_KEYS) + 1),
msg='Plasma description lacks necessary'
' density and/or temperature profiles for all components.')
self.assertIsInstance(
actual.profiles.axes[0],
pandas.Int64Index,
msg='Expected data type of X - axis for profiles is Int64Index.')
self.assertIsInstance(
actual.profiles.axes[1],
pandas.MultiIndex,
msg='Expected data type of Y - axis for profiles is MultiIndex.')
for key in range(len(actual.profiles.keys())):
self.assertTupleEqual(
actual.profiles.keys()[key],
self.EXPECTED_PROFILES_KEYS[key],
msg='Profiles key description fails for test case.')
def test_analytical_solver(self):
with self.assertRaises(NotImplementedError):
actual = Beamlet(solver='analytical')
def test_numerical_solver(self):
self.assertTupleEqual(
self.beamlet.profiles.shape,
(self.EXPECTED_PROFILES_LENGTH,
2 * len(self.EXPECTED_COMPONENTS_KEYS) + 1 +
self.beamlet.atomic_db.atomic_ceiling),
msg=
'Numerical solver failed to provide expected output into plasma profiles.'
)
for key_index in range(2 * len(self.EXPECTED_COMPONENTS_KEYS) + 1,
len(self.beamlet.profiles.keys())):
self.assertEqual(
self.beamlet.profiles.keys()[key_index][0],
'level ' + self.beamlet.atomic_db.inv_atomic_dict[
key_index - 2 * len(self.EXPECTED_COMPONENTS_KEYS) - 1],
msg=
'Pandas keys for labeling electron population evolution on atomic levels fails.'
)
for level in range(self.beamlet.atomic_db.atomic_ceiling):
self.assertIsInstance(self.beamlet.profiles[
'level ' + self.beamlet.atomic_db.inv_atomic_dict[level]],
pandas.core.series.Series,
msg='Expected data type of beam evolution '
'process are pandas series.')
self.assertEqual(
len(self.beamlet.profiles[
'level ' + self.beamlet.atomic_db.inv_atomic_dict[level]]),
self.EXPECTED_PROFILES_LENGTH,
msg='Beam evolution calculation are expected to return '
'atomic state evolution on the input grid.')
def test_not_supported_solver(self):
with self.assertRaises(Exception):
actual = Beamlet(solver='not-supported')
def test_attenuation_calculator(self):
self.beamlet.compute_linear_density_attenuation()
self.assertEqual(
self.beamlet.profiles.keys()[-1][0],
self.EXPECTED_ATTENUATION_KEY,
msg='Beam attenuation key mismatch within pandas data frame.')
self.assertIsInstance(
self.beamlet.profiles[self.EXPECTED_ATTENUATION_KEY],
pandas.core.series.Series,
msg=
'Beam attenuation output expected to be stored in pandas series.')
self.assertEqual(
len(self.beamlet.profiles[self.EXPECTED_ATTENUATION_KEY]),
self.EXPECTED_PROFILES_LENGTH,
msg=
'Beam attenuation calculation is expected to be returned on the input grid.'
)
test = self.beamlet.profiles['level 2s']
for level in range(1, self.beamlet.atomic_db.atomic_ceiling):
test += self.beamlet.profiles[
'level ' + self.beamlet.atomic_db.inv_atomic_dict[level]]
for index in range(self.EXPECTED_PROFILES_LENGTH):
self.assertEqual(
test[index],
self.beamlet.profiles[self.EXPECTED_ATTENUATION_KEY][index],
msg='Beam attenuation calculation fails for test case.')
def test_spontaneous_emission_fail(self):
with self.assertRaises(Exception):
self.beamlet.profiles[self.EXPECTED_ATTENUATION_KEY].\
compute_linear_emission_density(to_level=self.INPUT_TRANSITION[1], from_level=self.INPUT_TRANSITION[0])
def test_not_supported_atomic_level_fail(self):
with self.assertRaises(Exception):
self.beamlet.profiles[self.EXPECTED_ATTENUATION_KEY].\
compute_linear_emission_density(to_level=self.INPUT_TRANSITION[2], from_level=self.INPUT_TRANSITION[3])
def test_emission_calculator(self):
self.beamlet.compute_linear_emission_density(
to_level=self.INPUT_TRANSITION[0],
from_level=self.INPUT_TRANSITION[1])
self.assertEqual(
self.beamlet.profiles.keys()[-1][0],
self.INPUT_TRANSITION[1] + '-->' + self.INPUT_TRANSITION[0],
msg=
'Beam emission calculation key mismatch within pandas data frame.')
self.assertIsInstance(
self.beamlet.profiles[self.INPUT_TRANSITION[1] + '-->' +
self.INPUT_TRANSITION[0]],
pandas.core.series.Series,
msg='Beam emission output expected to '
'be stored in pandas series.')
self.assertEqual(
len(self.beamlet.profiles[self.INPUT_TRANSITION[1] + '-->' +
self.INPUT_TRANSITION[0]]),
self.EXPECTED_PROFILES_LENGTH,
msg='Beam emission calculation is expected to be returned '
'on the input grid.')
test = self.beamlet.profiles[
'level ' + self.
INPUT_TRANSITION[1]] * self.beamlet.atomic_db.spontaneous_trans[
self.beamlet.atomic_db.atomic_dict[self.INPUT_TRANSITION[0]],
self.beamlet.atomic_db.atomic_dict[self.INPUT_TRANSITION[1]]]
for index in range(len(test)):
self.assertEqual(
test[index],
self.beamlet.profiles[self.INPUT_TRANSITION[1] + '-->' +
self.INPUT_TRANSITION[0]][index],
msg='Beam emission calculation fails for test case.')
def test_relative_population_calculator(self):
self.beamlet.compute_relative_populations(
reference_level=self.INPUT_TRANSITION[0])
self.assertTupleEqual(
self.beamlet.profiles.filter(like='rel.pop').shape,
(self.EXPECTED_PROFILES_LENGTH,
self.beamlet.atomic_db.atomic_ceiling),
msg=
'Relative populations calculated do not match input level number.')
for level in range(self.beamlet.atomic_db.atomic_ceiling):
for index in range(len(self.beamlet.profiles)):
if self.beamlet.atomic_db.inv_atomic_dict[
level] == self.INPUT_TRANSITION[0]:
self.assertEqual(
self.beamlet.profiles['rel.pop ' +
self.beamlet.atomic_db.
inv_atomic_dict[level]][index],
1.0,
msg='Values on reference level are expected to be 1.')
else:
self.assertLess(
self.beamlet.profiles['rel.pop ' +
self.beamlet.atomic_db.
inv_atomic_dict[level]][index],
1.0,
msg=
'Values on comparative levels are expected to be less than 1.'
)
def test_beamlet_pandas_copy(self):
actual = self.beamlet.copy(object_copy='full')
self.assertTupleEqual(
actual.components.shape,
self.beamlet.components.shape,
msg=
'Actual and copy Beamlet object components are expected to have same shape.'
)
logic_components = actual.components == self.beamlet.components
self.assertTrue(
logic_components.values.all(),
msg='Content of actual and reference Beamlet components '
'objects is required to be equal.')
self.assertTupleEqual(
actual.profiles.shape,
self.beamlet.profiles.shape,
msg=
'Actual and copy Beamlet object profiles are expected to have the same shape.'
)
logic_profiles = actual.profiles == self.beamlet.profiles
self.assertTrue(logic_profiles.values.all(),
msg='Content of actual and reference Beamlet profiles '
'objects is required to be equal.')
def test_beamlet_pandas_copy_without_results(self):
actual = self.beamlet.copy(object_copy='without-results')
self.assertTupleEqual(
actual.components.shape,
self.beamlet.components.shape,
msg=
'Copy and Actual Beamlet object components are expected to have same shape.'
)
logic_components = actual.components == self.beamlet.components
self.assertTrue(logic_components.values.all(),
msg='Content of Copy and Actual Beamlet components '
'objects is required to be equal.')
self.assertEqual(
actual.profiles.shape[0],
self.beamlet.profiles.shape[0],
msg=
'Copy and Actual of Beamlet profiles are expected to have the same number of elements.'
)
self.assertEqual(
actual.profiles.shape[1],
self.beamlet.profiles.shape[1] -
self.beamlet.atomic_db.atomic_ceiling,
msg=
'Copy of Actual Beamlet object profiles is expected to have nr of atomic levels: '
+ str(self.beamlet.atomic_db.atomic_ceiling) + ' less columns.')
self.assertEqual(
actual.profiles.filter(like='level').shape[1],
0,
msg=
'The copy without results is expected NOT to contain any columns labeled <level>.'
)
def setUp(self):
self.beamlet = Beamlet()
def test_not_supported_solver(self):
with self.assertRaises(Exception):
actual = Beamlet(solver='not-supported')
def test_analytical_solver(self):
with self.assertRaises(NotImplementedError):
actual = Beamlet(solver='analytical')